Upload
others
View
3
Download
0
Embed Size (px)
Citation preview
HAL Id: hal-00297919https://hal.archives-ouvertes.fr/hal-00297919
Submitted on 12 Sep 2007
HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.
L’archive ouverte pluridisciplinaire HAL, estdestinée au dépôt et à la diffusion de documentsscientifiques de niveau recherche, publiés ou non,émanant des établissements d’enseignement et derecherche français ou étrangers, des laboratoirespublics ou privés.
Modelling CH4 emissions from arctic wetlands: effectsof hydrological parameterization
A. M. R. Petrescu, J. C. van Huissteden, M. Jackowicz-Korczynski, A.Yurova, T. R. Christensen, P. M. Crill, T. C. Maximov
To cite this version:A. M. R. Petrescu, J. C. van Huissteden, M. Jackowicz-Korczynski, A. Yurova, T. R. Christensen, etal.. Modelling CH4 emissions from arctic wetlands: effects of hydrological parameterization. Biogeo-sciences Discussions, European Geosciences Union, 2007, 4 (5), pp.3195-3227. �hal-00297919�
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Biogeosciences Discuss., 4, 3195–3227, 2007
www.biogeosciences-discuss.net/4/3195/2007/
© Author(s) 2007. This work is licensed
under a Creative Commons License.
BiogeosciencesDiscussions
Biogeosciences Discussions is the access reviewed discussion forum of Biogeosciences
Modelling CH4 emissions from arctic
wetlands: effects of hydrological
parameterization
A. M. R. Petrescu1, J. C. van Huissteden
1, M. Jackowicz-Korczynski
2, A. Yurova
2,
T. R. Christensen2, P. M. Crill
3, and T. C. Maximov
4
1Vrije Universiteit, Faculty of Earth and Life Sciences, Department of Hydrology and
Geo-Environmental Sciences, De Boelelaan 1085, 1081 HV, Amsterdam, The Netherlands2Lund University, Department of Physical Geography and Ecosystems Analysis, Solvegatan
12, 22362 Lund, Sweden3Stockholm University, Department of Geology and Geochemistry, Svante Arrhenius vag 8 C,
Frescati, 106 91 Stockholm, Sweden4Russian Academy of Sciences, Siberian Division, Institute of Biological Problems of
Cryolithozone, 41, Lenin Prospekt., Yakutsk, Sakha Republic, 677980 Russia
Received: 24 August 2007 – Accepted: 7 September 2007 – Published: 12 September 2007
Correspondence to: A. M. R. Petrescu ([email protected])
3195
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Abstract
This study compares the CH4 fluxes from two arctic wetland sites of different annual
temperatures during 2004 to 2006. The PEATLAND-VU model was used to simulate
the emissions. The CH4 module of PEATLAND-VU is based on the Walter-Heimann
model. The first site is located in northeast Siberia, Indigirka lowlands, Kytalyk reserve5
(70◦N, 147
◦E) in a continuous permafrost region with mean annual temperatures of
–14.3◦C. The other site is Stordalen mire in the eastern part of Lake Tornetrask (68
◦N,
19◦E), ten kilometres east of Abisko, northern Sweden. It is located in a discontinuous
permafrost region. Stordalen has a sub arctic climate with a mean annual temperature
of –0.7◦C.10
Model input consisted of observed temperature, precipitation and snow cover data.
In all cases, modelled CH4 emissions show a direct correlation between variations
in water table and soil temperature variations. The differences in CH4 emissions be-
tween the two sites are caused by different climate, hydrology, soil physical properties,
vegetation type and NPP.15
For Kytalyk the simulated CH4 fluxes show similar trends during the growing sea-
son, having average values for 2004 to 2006 between 1.29–2.09 mg CH4m−2
h−1
. At
Stordalen the simulated fluxes show a slightly lower average value for the same years
(3.52 mg CH4 m−2
h−1
) than the observed 4.7 mg CH4 m−2
h−1
. The effect of the longer
growing season at Stordalen is simulated correctly.20
Our study shows that modelling of arctic CH4 fluxes is improved by adding a relatively
simple hydrological model that simulates the water table position from generic weather
data. We conclude that CH4 fluxes at these sites are less sensitive to temperature
variation than to water table variations. Furthermore, parameter uncertainty at site
level in wetland CH4 process models is an important factor in large scale modelling of25
CH4 fluxes.
3196
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
1 Introduction
Together with water vapour and carbon dioxide (CO2), CH4 is an important contributor
to the warming of the atmosphere. The atmospheric mixing ratios of so called green-
house gases, CO2, and nitrous oxide (N2O) have increased about 31%, and 17%, re-
spectively above pre-industrial values whereas CH4 has increased 151%±25%, (Wat-5
son et al., 2001). The concentration of atmospheric CO2 has increased from a pre-
industrial value of about 280 ppm to 379 ppm in 2005. Increases in atmospheric CO2
since pre-industrial times are responsible for a radiative forcing of +1.66±0.17 Wm−2
(Solomon et al., 2007).
The N2O concentration in 2005 was 319 ppb, about 18% higher than its pre-industrial10
value. Nitrous oxide increased approximately linearly by about 0.8 ppb yr−1
over the
past few decades and contributes a radiative forcing of +0.16±0.02 Wm−2
and is due
primarily to human activities, particularly agriculture and associated land use change
(Solomon, et al., 2007).
The CH4 abundance in 2005 of about 1774 ppb is more than double its pre-industrial15
value.Increases in atmospheric CH4 concentrations since pre-industrial times have
contributed a radiative forcing of +0.48±0.05 Wm−2
. Current atmospheric CH4 levels
are due to continuing anthropogenic emissions of CH4, which are greater than natural
emissions. Emissions from individual sources of CH4 are not as well quantified as the
total emissions but are mostly biogenic and include emissions from wetlands, ruminant20
animals, rice agriculture and biomass burning, with smaller contributions from industrial
sources including fossil fuel-related emissions (Solomon et al., 2007).
About 60% of global CH4 missions come from human-influenced sources and the
rest are from natural sources (Houghton et al., 2001). Natural sources include wet-
lands, termites, oceans, and hydrates. Natural sources are dominated by wetlands.25
Where soils are waterlogged and oxygen is absent, methanogenic micro-organisms
produce large amounts of CH4 as they respire organic matter to CO2 to derive energy.
Wetland CH4 emissions are thought to comprise around 80 percent of the total natural
3197
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
CH4 source. Total annual CH4 emissions from natural sources are estimated to be
around 250 Tg (Reay, 2006).
In the past decade the overall annual rate of CH4 growth has decreased and be-
come highly variable (Dlugokencky et al., 2003; Ciais et al., 2005). Ciais et al. (2005)
attributes the decrease to a temporary reduction in anthropogenic emissions and the5
increased variability to wetland emission distribution. The largest CH4 atmospheric
mixing ratios are north of 40◦N (Steele et al., 1987). This distribution coincides with
the concentration of wetlands in the northern hemisphere and suggests that wetlands
in this area may make a significant contribution to the global CH4 budget (Moore and
Knowles, 1990; Aselmann and Crutzen, 1989; Crill et al., 1988; Matthews and Fung,10
1987).
The magnitude of the CH4 emissions from wetlands is controlled by the dynamic bal-
ance between CH4 production and oxidation rates in the peat profile and by transport
mechanisms, (Bubier and Moore, 1994). Measured emissions demonstrate high spa-
tial and temporal variation (Moore et al., 1990; Whalen and Reeburg, 1992; Dise, 1993)15
linked to environmental factors such as variation in temperature and ground water level.
CH4 production and oxidation rates depend on substrate availability and supply, tem-
perature and activity of the CH4-producing and CH4-oxidizing bacteria, affected by the
redox status in the soilmatrix which in turn is linked to the soilmoisture condition and hy-
drochemistry, (Kettunen et al., 1999). Changes in both substrate availability and oxida-20
tion state during the growing season affect the population dynamics of methanogenic
and methanotrophic bacteria (Svensson and Rosswall, 1984; Whiting and Chanton,
1993) and are reflected in the net CH4 flux (Kettunen et al., 1999).
The water table in many wetlands show a seasonally related variation, with low levels
in midsummer when the evapotranspiration is high and high levels in the rest of the25
season when precipitation dominates. The amount of variation depends on the water
sources of the wetland (precipitation, groundwater or surface water flow). Because of
the presence of microtopography (hummocks, hollows and lawns, Bubier et al., 1993b)
the topography of a wetland has a very high variability in space close related to the
3198
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
water table. Bubier et al. (1993b) found that the CH4 flux follows the trend: hollows >
lawns > hummocks. We study these sites because the hollows nutrient-rich and often
saturated river delta (lawns) have CH4 much higher than the other microlandscapes.
A characteristic of high latitude wetlands is the presence of the permafrost. Studies
have shown that approximately 14% of the global carbon is stored in permafrost soils5
and sediments (Post et al., 1982). The frozen subsoil contributes to waterlogged soil
conditions in permafrost wetlands. However, observations have shown that permafrost
degradation causes an increase of methane fluxes by changes in local hydrology and
ecosystem balance. More widespread thaw across the discontinuous permafrost re-
gion will be an important consideration to boreal C budgets with future climate change10
(Turetsky et al., 2002). Adequate modelling of these processes requires first of all cor-
rect modelling of the effects of water table on CH4 fluxes. Models also should perform
well in situations where ground water table observations are not available.
The purpose of this study is to make a comparison between an arctic (Kytalyk,
Siberia) and subarctic (Stordalen, Sweden) wetland and their seasonal CH4 fluxes,15
and to test a flux model that combines the CH4 flux process approach of Walter (2000)
with the soil physics as included in the model of Granberg et al. (1999). The study is
based on site soil physical, vegetation and water level data. The CH4 flux measure-
ments at the sites have been used to validate the model. Model runs have been made
with both site water level observations and modelled water levels based on generic20
weather data, to compare the influence of modelled or observed water tables on model
performance.
2 Material and methods
2.1 Site description
Kytalyk. The study area on which the research was based on is located in Northeastern25
Siberia, in the Kytalyk reserve, in the Indigirka lowlands near Chokurdakh (70◦48
′N,
3199
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
147◦26
′E, elevation 48 m). The research area consists of three different morphological
units: the river floodplain, the river terrace with tundra vegetation and the high plateaus
(10–30 m) underlain by continuous permafrost. The area is characterized by silty soils
with a peaty topsoil. The study site is located in river lowlands consisting of fluvial ter-
races of Late Pleistocene and Holocene age, and the recent floodplain of a meandering5
river with extensive backswamps situated behind natural levees. Next to the floodplain,
a terrace (Holocene age) approximately 2 m above the present floodplain is found, con-
sisting of a drained thermokarst lake floor, with consisting of hummocky moist tundra in
the dryer parts and a mature network of low-centred ice wedge polygons in the lower
parts. The next higher level in the landscape consists of so-called “ice complex” hills,10
which probably represent a higher Pleistocene terrace. The CH4 flux measurements
were confined to the lower terrace and the river floodplain. The climate is high arctic,
with an annual average temperature measured at the Chokurdakh airport weather sta-
tion of –14.3 degrees Celsius, the warmest month being July, the coldest January (data
derived from NOAA website and summarized by Van Huissteden et al., 2006b).15
At Kytalyk, The vegetation of the lower terrace/drained thaw lake consists mainly of
ombrotrophic Sphagnum mire, alternating with interconnected depressions dominated
by sedges and Eriophorum. On the dryer parts Betula nana, Salix and Eriophorum
hummocks dominate. On the river floodplain vegetation varies from Carex /Eriophorum
fen with grasses in wide backswamp areas, to Salix shrub on levees. The active layer20
ranges from 18 cm at dry, Sphagnum-covered sites on the terrace, to up to 53 cm in
some parts of the floodplain. Thermokarst processes are active along the river bank
and thermokarst lake banks.
Stordalen. The Stordalen Mire (68◦21
′N, 19
◦02
′E, elevation 360 m a.s.l.) is situated
at about 10 km east of Abisko Scientific Research Station, Sweden (Oquist et al., 2001).25
This mire was part of the International Biological Programme, and has been studied
since early 1970s. The site is about one kilometer from and ten meters above Lake
Tornetrask.
The entire Stordalen mire is 25 ha large and is treeless. It is made up of four ma-
3200
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
jor habitats: (1) elevated, nutrient-deficient (ombrotrophic) areas with hummocks and
small shallow depressions; (2) wet, nutrient-richer (minerotrophic) depressions; (3)
pools and (4) brooks bringing water to and from the complex (Rooswall et al., 1975).
With regard to the permafrost and the plant cover composition, the site is a typical
northern peatland. The elevated parts are on permafrost and tundra like vegetation5
(Rooswall et al., 1975).
The climate is subarctic, with a mean annual temperature of –0.7◦C, the warmest
month being July and coldest February. The annual precipitation at Abisko is the lowest
in the northern part of Sweden, about 300 mm (records from 1913–2003).
This study focuses on a wet minerotrophic area of the mire, where the water table is10
situated in the vicinity of the soil surface and the vegetation is dominated by Eriophorum
angustifolium. In the drier parts of the mire the Eriophorum vaginatum and Carex
rotundata dominates the Sphagnum spp. (Oquist and Svensson 2001).
2.2 Measurements
CH415
Kytalyk. During 2004–2006, the CH4 fluxes were measured in Kytalyk in short (few
days) field campaigns during the summer period. The flux measurements were made
using closed chambers, in a roving manner, in order to sample a wider variety of veg-
etation type and hydrologic conditions. (Van Huissteden et al., 2005; Van der Molen et
al.,2007).20
Stordalen. CH4 fluxes were measured using the closed chambers technique (Chris-
tensen, 1993, 1995). The automatic chamber system at the Stordalen Mire is similar to
the system described in detail by Goulden and Crill (1997). The measurement of CH4
was made manually. Samples of the chamber headspace air were taken from the main
sample air flow downstream from the gas analyzers.25
3201
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Water table measurements and simulations
Kytalyk. The ground water table was determined after the flux measurements took
place, from a hand auger hole. During the summer of 2004 daily values were recorded
during four consecutive days (27–31 July) (Van Huissteden et al., 2005). For the year,
2005, measurements took place between 20 and 30 July. In 2006 the water table was5
measured from 15 to 18 August.
Stordalen . Water table position relative to ground level was measured manually 3–5
times per week at all sites (Backstrand et al., 2007).
2.3 Model description
2.3.1 The PEATLAND-VU Model10
PEATLAND-VU is a process-based model of CO2 and CH4 emission from peat soils
at various management scenarios. It includes a slightly modified version of the Walter
(2000) soil profile scale CH4 flux model (Van Huissteden et al., 2006a) and a simplified
soil physical model to simulate soil temperatures and soil freezing/thawing.
It consists of four submodels: a soil physics submodel to calculate temperature,15
water saturation and ice content of the soil layers, a CO2 submodel, a CH4 submodel
and an organic production submodel (Van Huissteden et al., 2006a).
The CH4 submodel is based on Walter et al. (1996), Walter (2000) and Bogner et
al. (2000). The model of Walter (2000) includes: (1) CH4 production depending on
substrate availability; (2) CH4 oxidation within the aerated soil topsoil and in plant roots20
and stems; (3) CH4 transport by diffusion above and below the water table; (4) transport
by ebullition below the water table; and (5) transport through plants (Van Huissteden et
al., 2006a). For this study we only used PEATLAND-VU to estimate CH4 fluxes.
The model requires as input a soil profile description with organic matter content, dry
bulk density and pF curves for each soil horizon, and time series for soil surface or air25
temperature, water table depth and snow cover for each model time step (1 day in this
3202
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
study). Output of the model is the surface CH4 fluxes, including contributions from the
different transport pathways.
2.3.2 Input data and parameterization of the model
The input data for PEATLAND-VU Model can be obtained from generic data, e.g. soil
profiles and weather data stations (Van Huissteden et al., 2006a). Several soil param-5
eters, in particular those relating to organic matter quality and quantity, are hard to
measure; therefore model optimization may be necessary.
Based on the input data, simulations were carried out and the output CH4 fluxes were
compared with the measured ones (only for the Kytalyk site: three values represented
with error bars). All input data (climate, soil parameters, vegetation type and ground10
water depth) were specific for the site.
For 2004 to 2006, the Stordalen climatic data sets were provided by the Abisko Sci-
entific Research Station. For Kytalyk the data were obtained from Chokurdakh weather
station at the local airport. In addition, air and soil temperature data measured on the
site for micrometeorological CO2 and H2O flux measurements were used (Van der15
Molen et al., 2007). Several parameters influence the simulations and were calibrated.
The most important ones were: the CH4 production rate R0 was set at the low end of
the range indicated by Walter (2000) (Van Huissteden et al., 2006a). For Kytalyk the
value was set to 0.3µMh−1
and for Stordalen to 0.25 µMh−1
for both WT approaches;
the Q10 value for temperature correction CH4 production (range 1.7–16 in Walter and20
Heimann 2000) was set at a value of 4 for the Swedish site and 2 (simulations with
observed WT) and 3 (simulations with simulated WT) for the Siberian site; and the CH4
plant oxidation fraction was set 0.6 for the Siberian site and 0.7 for the Swedish site.
2.3.3 Water table simulations
The ground water table strongly influences the methane fluxes. Two runs were per-25
formed with two different water table files. The first was the measured water table
3203
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
and the second was simulated using equations based on the Mixed Mire Water and
Heat Model (MMWH) of Granberg et al. (1999) as modified by Yurova et al., 2007).
The hydrology of the model is represented by a simple bucket approach describing the
change in water content of a unit area (Granberg et al., 1999). MMWH model was
developed to reconstruct the water table position in the upper active layer of the boreal5
mixed mires. Approach is based on the steady state moisture distribution in the un-
saturated zone, which is simulated by the van Genuchten functions (1980) simplified
and parameterized for the peat of different types by Weiss et al. (1998). The lateral
flow is model dynamically, including the transmissivity feedback: the increase in runoff
associated with higher water table due to change in hydraulic conductivity (maximum10
at the surface and reduces strongly with depth). Calculated potential evapotranspira-
tion is reduced when the water table drops below the peat surface, and this decrease
is exponential with a water table depth. The depth of permanent saturation and peat
composition and physical properties are the main site-specific model parameters.
3 Results15
3.1 Annual climate variations
Stordalen. The variation in climate parameters for 2004–2006 is shown in Fig. 3. The
average value for air temperature was 1.07◦C, the coldest day being the 3 March 2006
(–29.36◦C) and warmest the 5 July 2005 (19.69
◦C). The data were provided by the
Abisko Scientific Research Station for the three years in study. Abisko is in the rain20
shadow of the Norwegian mountains and the precipitation received is among the lowest
in Scandinavia (Johansson et al., 2006). The mean annual precipitation for the period
2004–2006 is only 612 mm. The gaps in data for the soil temperature at 3 cm depth
were due to the malfunction of the instrument.
The winter precipitation is mainly snow. The mean snow depth on the Stordalen mire25
was during this period 0.18 m. This is different from Abisko, due to snowdrift effects in
3204
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
the open space of the Stordalen mire. The soil temperature records were measured at
Stordalen mire.
Kytalyk. Figure 4 shows the three years record for climate parameters at the Siberian
site. The mean temperature for the three years was –12.8◦C, the coldest day being 12
December 2004 and the warmest 4 July 2005. The source for the air temperature, pre-5
cipitation and snow data were the local site measurements in summer, supplemented
with data from the Chokurdakh airport weather station. Missing values were interpo-
lated.
3.2 Water table and active layer measurements
Stordalen . Water table position relative to ground level was measured manually 3–510
times per week at all sites (Backstrand et al., 2007). For this study the water levels
from the fen portion of the mire were used, as presented in Fig. 5.
The active layer was measured at Stordalen mire at different sites, from 17 June–20
September 2004 and on the 22 September 2005 at 121 sites. The mean value for the
year 2004 was 50.67 cm and for 2005 was 66.6 cm.15
Kytalyk . The water table measurements (Table 2 and Fig. 8) were made during the
field campaigns. We used the average water table for the floodplain sites to interpolate
between periods with modelled water table. In Table 2 the averaged values (7 point
measurements in 2004, 21 in 2005 and 12 in 2006 from the floodplain wet area) are
shown.20
Using as input parameters the climate data, we modelled the water table with the
MMWH model (Granberg et al., 1999, modified by Yurova et al., 2007). Fig. 6 shows
the simulation for Stordalen mire and Fig. 7 for Kytalyk site.
The cause of the deviation between data and model for the Kytalyk simulations is the
excessive drainage of the floodplain caused by an abnormal low water level of the river25
water in 2005. On the terrace surface, where the effects of the low river water level
have been absent, the measured water table for 2005 agrees better with the model
(measured WT –0.2+/–1.22).
3205
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
3.3 CH4 fluxes
Stordalen. Using the measured water table depth from the fen part of the Stordalen
Mire, the CH4 flux trend is similar to the simulated one. The range for the measured
CH4 is between 0 mg m−2
h−1
and 18.07 mg m−2
h−1
(average value of 4.7 mg m−2
h−1
),
while the simulated emissions vary between 0 mg m−2
h−1
and 26.9 mg m−2
h−1
, with5
an average value for the three years of 3.52 mg m−2
h−1
(Fig. 8).
A second run, using the simulated water table from the changed version of Granberg
et al. (1999), was performed with the PEATLAND-VU model. The CH4 fluxes show
a very similar pattern for the years 2004 to 2006 (see Fig. 8). The measured CH4
emissions from the fen portion of the mire, averaged a value of 4.7 mg m−2
h−1
(data10
from two chambers for the 2004 and 2005 years and measured data with TDL for
2006) and range between 0 mg m−2
h−1
and 18.07 mg while the simulated fluxes range
between 0 mg m−2
h−1
and 18.54 mg m−2
h−1
with averaged value of 2.53 mg m−2
h−1
.
The CH4 flux peak in both model and data was during the same month (September)
and the period with active emission coincides with the growing season (April–October).15
Kytalyk . For Kytalyk the measurements for the water table depth were done for four
consecutive days in 2004, 10 days in 2005 and four day in 2006. Due to the very remote
area was not possible to perform yearly measurements, therefore the water table input
file used by PEATLAND-VU was constructed based on the available data and on the
assumption that the minimum water depth is 5 cm below ground and does not exceeds20
15 cm depth during winter time. The active layer was simulated with PEATLAND-VU
based on the output temperature file constructed by the model using the air tempera-
ture as input. The soil physical submodel tends to overestimate the active layer depth.
However, the measured active layer average value at the wet sites (0.45 cm) is within
the range of the simulated ones (0.05–0.85 m).25
The CH4 fluxes range between 0 mg m−2
h−1
and 20.8 mg m−2
h−1
with a three year
average value of 1.29 mg m−2
h−1
. For the 2005 and 2006 the averaged value matches
with the simulations. The only exception is for the year 2004 when the measurement
3206
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
exceeds the simulation but it is with the error measurements (Fig. 10).
Running PEATLAND-VU with simulated water table file, the results show a good
match with the averaged point measurements (Fig. 11). The fluxes vary between
0 mg m−2
h−1
and 26 mg m−2
h−1
, with a three year average flux of 2.09 mg m−2
h−1
.
Similar to the simulations carried out with the measured water table, the active layer5
averaged value (0.45 cm) is within the range of the simulated one (0.05–0.85 m).
4 Discussion
Previous studies show that the CH4 emissions are highly influenced by the water table
variation (Van Huissteden et al., 2005). Therefore, for a better estimation of the total
CH4 emission from arctic areas, it is necessary to have a very good estimation of the10
water table depth. With the global warming, the permafrost areas are melting and
disappearing, as it is the case of Stordalen mire (Christensen et al., 2004).
For the Swedish site, Stordalen, the CH4 emissions on a decadal time scale are
mainly influenced by the temperature changes in the past decades, which induced the
melt of the permafrost. This results in an increase in the active layer depth and variation15
in the water table dynamics. With a wetter condition, the vegetations shifted from shrub
dominated, elevated, ombrotrophic conditions to wet graminoid dominated more nutri-
ent rich or minerotrophic conditions (http://www.geography.uc.edu/∼kenhinke/CALM).
Such trend it is observed at Stordalen but less dramatic (Christensen et al., 2004). The
vegetation composition has changed significantly with a decrease in the permafrost-20
dependent relatively dry elevated mire vegetation types and a corresponding increase
in the lower wet graminoid dominated vegetation. This change corresponds with
changes in the underlying permafrost distribution as the latter is determining the mire
surface topography and hydrology, and hence the plant community structure (Chris-
tensen et al., 2004). Due to this change the CH4 emissions increased from 1.8–25
2.2 mg m−2
h−1
(1970) (Christensen et al., 2004) to 4.7 mg m−2
h−1
(averaged mea-
sured CH4 flux 2004–2006).
3207
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
The simulated CH4 fluxes for Stordalen range between 3.52 mg CH4 m−2
h−1
(mea-
sured WT) and 2.53 mg CH4 m−2
h−1
(simulated WT), while for Siberia the mean tem-
perature for the three years in case was –12.8◦C and the averaged simulated CH4
fluxes were much lower than the Swedish ones (1.29 mg CH4 m−2
h−1
with measured
WT and 2.09 mg CH4 m−2
hr−1
with simulated WT). The mean soil temperature at the5
Stordalen site, for the years 2004–2006 was +3.76◦C. This is in accordance with the
known sensitivity of methanogenesis to temperature (Walter, 2000). However methane
formation also may occur at subzero temperatures (Rivkina et al., 2000; Wagner et al.,
2007) winter emissions that may occur at subzero temperatures are not included in the
measurement data and the model.10
The optimization of the methane model input parameters (CH4 R0 production rate,
Q10 value for temperature correction CH4 production) was done by optimizing the val-
ues until the optimum match between data and model was found. For both sites the
plant oxidation factor was set to a value of 0.7. This means that 70 percent of the
methane is oxidized during the plant transport. For simulations at Stordalen mire a15
Q10 value of 4 was used, while for Kytalyk the value was set to 2, the range of it be-
ing 1.7–16 (Walter, 2000). Together with R0, the Q10 value influences the peak of the
summer emissions relative to early and autumn. Since at Kytalyk no data throughout
the growing season are available, tuning of the model parameters was focused on R0
rather than Q10. In general, the model is not very sensitive to small differences in the20
value of Q10. We conclude that the model is more sensitive to the water table than to
the temperature. This high sensitivity for water table position agrees well with statisti-
cal analysis of CH4 flux data, soil temperatures and water table data from Kytalyk (Van
Huissteden et al., 2005).
A good match was observed between the simulated and measured CH4 fluxes us-25
ing the simulated WT. One of the reasons might be a continuous water table file with
constant fluctuations from summer to winter throughout the three years in study.
For the Kytalyk site, the simulated CH4 fluxes match in both approaches with the av-
eraged point measured CH4. The fluxes are much lower than the ones from N Sweden
3208
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
and this may be due to: (1) shorter growing season (May–September) compared with
a longer one at Stordalen (April–October), (2) lower soil temperature, (3) more Sphag-
num vegetation which lives in symbiosis with metanotrophic bacteria and consumes
the CH4 below the water table (Raghoebarsing et al., 2005) while the Stordalen wet
site has Carex and Eriophorum spp., and (4) differences within the active layer depth.5
Vegetation related factors influencing the CH4 fluxes from floodplain are (1) plant
mediated transport of CH4 between the soils and atmosphere and (2) primary produc-
tivity (Van Huissteden et al., 2005). Sedges are good transporters of CH4 (Busch and
Losch, 1999). The CH4 fluxes are related to the vegetation by primary production by
providing substrate for methanogens through root exudation (King and Reeburg, 2002).10
A recent study at Stordalen shows that sites dominated by Eriophorum angustifloum
have higher CH4 fluxes than the ones with Eriophorum vaginatum or Carex rotundata
(Strom and Cristensen, 2007).
The variation within the CH4 fluxes is strongly influenced by the hydrological con-
ditions at each site. A smoother variation (see Fig. 8) is observed for Stordalen CH415
as the WT had a more constant trend (not many picks, Fig. 5). For the Siberian site
the water table varied a lot (wet in 2004 and very dry in 2005 caused by the excessive
drainage of the floodplain) therefore the emissions show a higher variability in time.
5 Conclusions
CH4 fluxes from arctic wetlands show a high variability in time. Even if both sites are20
located in arctic areas, the differences are considerable. Both study sites are wetlands
but the CH4 fluxes have different patterns. We hypothesize that the cause for these
differences are (1) water table depth (2) air and soil temperature (3) vegetation type and
(4) net primary production. By using the simulated water table depth, it was possible to
match the measured CH4 emissions with the simulated ones, using a relatively simple25
bucket model to simulate the water table based on generic meteorological precipitation
and temperature time series. The results of our study are promising for improvement
3209
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
of regional scale CH4 emission models. Parameter uncertainty at site level in wetland
CH4 process models is an important factor in large scale modelling of CH4 fluxes. The
CH4 fluxes at the Kytalyk site appear less sensitive to temperature variation than to
water table variation, theory in concordance with other studies (Moore et al., 1990;
Roulet et al., 1991; Walter et al., 1996; Van der Molen et al., 2007). This stresses5
the need for improvement of hydrological models for correct simulation of water table
variation in modelling of wetland CH4 fluxes.
Acknowledgements. I would like to thank J. C. van Huissteden for his support and commentson earlier drafts of this paper, all the people I meet in Sweden during my two months sec-ondment at the Department of Physical Geography and Ecosystems Analysis, Lund University,10
for their help, all co-authors for their precious comments and the reviewers for their thoughtfulsuggestions. I would also like to thank A. D. Friend for giving me the opportunity to go visit theKytalyk reserve in NE Siberia. This study is funded by Marie Curie Fellowship, GreencyclesRTN.
References15
Aselmann, I. and Cruzen P. J.: Global distribution of natural freshwater wetlands and ricepaddies, their net primary productivity, seasonality and possible CH4 emissions, J. Atmos.Chem., 8, 307–359, 1989.
Backstrand C., Crill, P. M., Mastepanov, M., Christensen, T. R., and Bastviken D.: NonmethaneVolatile Organic Compound Flux from a Subarctic mire in Northern Sweden. Master thesis20
at the Department of Geology and Geochemistry, Stockholm University, Sweden, 2007.Bubier, J., Costello, A., Moore, T. R., Roulet, N. T., and Savage, K.: Microtopography and CH4
flux in boreal peatlands, northern Ontario, Canada, Can. J. Bot., 71, 1056–1063, 1993b.Bubier, J. L. and Moore T. R.: An ecological perspective on CH4 emissions from northern
wetlands, Tree, 9, 409–464, 1994.25
Busch, J. and Losch R.: The gas exchange of Carex species from eutrophic wetlands and itsdependence on microclimatic and soil wetness conditions, Phys. Chem. Earth, Part B, 24,117–120, 1999.
3210
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Ciais, Ph., Reichstein, M., Viovy, N., Granier, A., Ogee, J., Allard, V., Aubinet, M., Buchmann,N., Bernhofer, Chr., Carrara, A., Chevallier, F., De Noblet, N., Friend, A. D., Friedlingstein,P., Grunwald, T., Heinesch, B., Keronen, P., Knohl, A., Krinner, G., and Loustau, D.: Europe-wide reduction in primary productivity caused by the heat and drought in 2003, Nature,437(7058), 529–533, 5p, 2 diagrams, 1 graph; doi:10.1038/nature03972; (AN 18373101),5
2005.Christensen, T. R.: CH4 emissions from Arctic tundra, Biogeochemistry, 21(2), 117–139, 1993.Christensen, T. R., Johansson S., Callaghan T. V., and Havstrom, M.: Spatial variation in high
latitude CH4 flux along a transect across Siberian and European tundra environments, J.Geophys. Res., 100(D10), 21 035–21 045, 1995.10
Christensen, T. R., Johansson T., Akerman H. J., et al.,: Thawing sub-arctic per-mafrost: effects on vegetation and CH4 emissions, Geophys. Res. Lett. 31, L04501,doi:10.1029/2003GL018680, 2004.
Crill, P. M., Bartlett, K. B., Hariss, R. C., Gorham, E., Verry, E. S., Sebacher, D. I., Madzar,L., and Sanner, W.: CH4 flux from Minnesota peatlands, Global Biogeochem. Cycles, 2,15
371–384, 1988.Dise, N. B.: CH4 emissions from Minnesota peatlands: spatial and seasonal variability, Global
Biogeochem. Cycles, 7, 123–142, 1993.Dlugokencky, E. J., Houweling, S., Bruhwiler, L., Masarie, K. A., Lang, P. M., Miller J. B., and
Tans, P. P.: Atmospheric CH4 levels off: Temporary pause or new steady state?, Geophys.20
Res. Lett., 30(19), 1992, doi:10.1029/2003GL018126, 2003.Goulden, M. L. and Crill P. M.: Automated measurements of CO2 exchange at the moss surface
of a black spruce forest, Tree physiology, 17, 537–542, 1997.Granberg, G., Grip, H., Lofvenius, M. O., Sundh I., Svensson, B. H., and Nillson M.: A simple
model for simulation of water content, soil frost, and soil temperatures in boreal mixed mires,25
Water Resour. Res., 35(12), 3771–3782, 1999.IPCC Third Assessment Report: Climate Change 2001 – Synthesis Report, Stand-alone edi-
tion, Watson, R.T. and the Core Writing Team (Eds.) IPCC, Geneva, Switzerland. pp 184,2001.
Johansson, T.: Temporal and spatial variability of carbon cycling in a subarctic landscape.30
Doctoral dissertation, Department of Physical Geography and Ecosystem Analysis, LundUniversity, 2006.
Kettunen, A., Kaitala, V., Lehtinen, A., Lohila, A., Alm, J., Solvola, J., and Martikainen, P. J.:
3211
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
CH4 production and oxidation potentials in relation to water table fluctuations in two borealmires, Soil Biol. Biochem., 31, 741–749, 1999.
King, J. Y. and Reeburg, W. S.: A pulse-labelling experiment to determine the contributionof recent plant photosynthates to net CH4 emissions in arctic wet sedge tundra, Soil. Biol.Biochem., 34, 173–180, 2002.5
Matthews, E. and Fung, I.: CH4 emissions from natural wetlands: global distribution, area andenvironment characteristics of sources, Global Biogeochem. Cycles, 1, 61–86, 1987.
Moore, T. R. and Knowles, R.: CH4 emissions from fen, bog and swamp peatlands in Quebec,Biogeochemistry, 11, 45–61, 1990.
NOAA-NCDC website http://lwf.ncdc.noaa.gov/oa/ncdc.html.10
Oquist, M. G. and Svensson, B. H.: Vascular plants as regulators of CH4 emissions from asubarctic mire ecosystem, J. Geophys. Res., 107(D21), 4580, doi:10.1029/2001JD001030,2002
Post, W. M., Emanuel, W. R., Zinke, P. J., and Stangenberger, A. G.: Soil carbon pools andworld life zones, Nature, 298, 22–54, 1982.15
Raghoebarsing, A. A., Smolders, A. J. P., Schmid, M. C., Rijpstra, W. I. C, Wolters-Arts, M.,Derksen, J., Jetten, M. S. M., Schouten, S., Sinninghe Damste, J. S., Lamers, L. P. M.,Roelofs, J. G. M., Op den Camp, H. J. M., and Strous, M.: Methanotrophic symbionts provideC for photosynthesis in peat bogs, Nature, 436, 1153–1156, 2005.
Reay, D. and Hughes, P.: “CH4”, in: Encyclopedia of Earth, edited by: Cutler, J. Cleveland20
(Washington, D.C.: Environmental Information Coalition, National Council for Science andthe Environment). [Published November 24, 2006; Retrieved January 22, 2007], 2006.
Rivkina, E. M., Friedmann, E. I., McKay, K. P., and Gilichinsky, D. A.: Metabolic activity ofpermafrost bacteria below the freezing point, Appl. Environ. Microbiol., 66(8), 3230–3233,2000.25
Rosswall, T. and Heal, O.W. (Eds.): Structure and Function of Tundra Ecosystems, Ecol. Bull.(Stockholm), 20, 265–294, 1975.
Roulet, N., Moore, T., Bubier, J., and Lafleur, P.: Northern fens: CH4 flux and climatic change,Tellus, 44B, 100–105, 1991.
Steele, L. P., Fraser, J. P., Rasmussen, R. A., Khalil, M. A. K., Conway, T. J., Crawford, A. J.,30
Gammon, R. H., Maserie, K. A., and Thoning, K. W.: The global distribution of CH4 in thetroposphere, J. Atmos. Chem., 5, 125–172, 1987.
Solomon, S., Qin, D., Manning, M., Alley, R. B., Berntsen, T., Bindoff, N. L., Chen, Z.,
3212
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Chidthaisong, A., Gregory, J. M., Hegerl, G. C., Heimann, M., Hewitson, B., Hoskins, B.J., Joos, F., Jouzel, J., Kattsov, V., Lohmann, U., Matsuno, T., Molina, M., Nicholls, N., Over-peck, J., Raga, G., Ramaswamy, V., Ren, J., Rusticucci, M., Somerville, R., Stocker, T. F.,Whetton, P., Wood, R. A., and Wratt, D.: Technical Summary. In: Climate Change 2007: ThePhysical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of5
the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning,M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge UniversityPress, Cambridge, United Kingdom and New York, NY, USA, 2007.
Strom, L. and Christensen T. R.: Below ground carbon turnover and greenhouse gas ex-changes in a sub-arctic wetland, Soil Biol. Biochem., 39(7), 1689–1698, 2007.10
Svensson, B. H. and Rosswall, T.: In situ CH4 production from acid peat in plant communitieswith different moisture regime in a subarctic mire, Oikos 43, 341–350, 1984.
Turetsky, M. R., Wieder, R. K., and Vitt, D. H.: Boreal peatland C fluxes under varying per-mafrost regimes, Soil Biol. Biochem., 34, 907–912, 2002.
Van Genuchten, M. T.: A closed form equation for predicting the hydraulic conductivity of un-15
saturated soils, Soil Sci. Soc. Am. J., 44(5), 892–898, 1980.Van Huissteden, J., Maximov, T. C., and Dolman, A. J.: High CH4 flux from an arc-
tic floodplain (Indigirka lowlands, Eastern Siberia), J. Geophys. Res., 110, G02002,doi:10.1029/2005JG000010, 2005.
Van Huissteden, J., Van den Bos, M., and MartcorenaAlvarez, I.: Modelling the effect of water-20
table management on CO2 and CH4 fluxes from peat soils, Netherlands J. Geosci., 85, 3–18,2006a.
Van Huissteden, J., Maximov, T. C., and Dolman, H.: CH4 fluxes in 2004 and 2005 in theNortheast Siberian tundra near Chokurdakh, Indigirka Lowlands, in: International workshopon H2O and CO2 exchange in Siberia, edited by: Dolman, H., Moors, E., Ohta, T., and25
Maximov, T. C., Nagoya, Japan, p. 33–36, 2006b.van der Molen, M. K., Van Huissteden, J. C., Parmentier, F. J., Petrescu, A. M. R., Dolman,
A. J., Maximov, T. C., Kononov, A. V., Karsanaev, S. V., and Suzdalov, D. A., The seasonalcycle of the greenhouse gas balance of a continental tundra site in the Indigirka lowlands,NE Siberia, Biogeosciences Discuss., 4, 2329–2384, 2007,30
http://www.biogeosciences-discuss.net/4/2329/2007/.Wagner, D., Gattinger, A., Embacher, A., Pfeiffer, E.-M., Schloter, M., and Lipski, A.:
Methanogenic activity and biomass in Holocene permafrost deposits of the Lena Delta,
3213
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Siberian Arctic and its implication for the global CH4 budget, Global Change Biology (On-line Accepted Articles), doi:10.1111/j.1365-2486.2007.01331.x, 2007.
Walter, B. P., Heimann, M., Shannon, R. D., and White, J. R.: A process based model to deriveCH4 emissions from natural wetlands. Report no. 215 Max-Planck-Institut fur Meteorologie(Hamburg), 21 pp, 1996.5
Walter, B. P. and Heimann, M.: A process-based, climate-sensitive model to derive CH4 emis-sions from natural wetlands: Application to five wetland sites, sensitivity to model parame-ters, and climate, Global Biogeochem. Cycles, 14, 745–765, 2000.
Whalen, S. C. and Reeburgh, W. S.: Interannual variations I tundra CH4 emissions: A four-yeartime series at fixed sites, Global Biogeochem. Cycles, 6, 139–159, 1992.10
Whiting, G. J. and Chanton, J. P.: Primary production control of CH4 emissions from wetlands,Nature, 364, 794–795, 1993.
Yurova, A., Annett W., Sagerfors J., and Nilsson M.: Variations in Net Ecosystem Exchange ofCarbon Dioxide in a Boreal Mire: Modelling Mechanisms Linked to Water Table Position, J.Geophys. Res., 112, G02025, doi:10.1029/2006JG000342, 2007.15
3214
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Table 1. Soil physical parameters per soil horizon as used in the PEATLAND-VU Model (VanHuissteden et al., 2006a; Rosswall and Heal, 1975).
Soil physical parameters per soil horizon Kytalyk Stordalen
Number of horizons 3 4Horizon base depths with respect to surface (in meters) [0.1, 0.2, 2.0] [0.1, 0.2, 0.3, 2.0]
C/N ratios for each soil layer [15, 15, 15] [48, 38, 31, 15]
Dry bulk density for each horizon (kg m−3
) [100, 130, 975] [88, 102, 519, 808]Percentage organic matter for each horizon [95.0, 80.0, 5.0] [90.0, 80.0, 70.0, 5.0]
pH [6.0, 6.0, 7.0] [4.0, 4.0, 4.1, 4.0]
3215
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Table 2. Average water table depth and active layer thickness (cm below ground) from thefloodplain wet area in Kytalyk for the years 2004–2006.
Year Average water table Average active layer thickness(cm below surface) (cm)
2004 0.71 42.82005 2.8 42.52006 0.16 53.5
3216
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
N
Figure 1. Location of the study site, Kytalyk Reserve, NE Siberia (modified after Van Fig. 1. Location of the study site, Kytalyk Reserve, NE Siberia (modified after Van Huisstedenet al., 2006a).
3217
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Fig. 2. Location of the study site, Stordalen mire, N Sweden (after Backstrand et al., 2007).
3218
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Figure 3. Three years weather data records from the Stordalen Mire (source: Abisko Fig. 3. Three years weather data records from the Stordalen Mire (source: Abisko ScientificResearch Station).
3219
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Fig. 4. Three years weather data records from the Kytalyk site derived from Chokurdakhairport weather station (source: NOAA-NCDC website http://lwf.ncdc.noaa.gov/oa/ncdc.html,augmented with local summer measurements).
3220
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
157 166 182 199 210 242−10
−5
0
WT 2004
148 168 176 194 205 214 221 235 252−5
0
5
10WT 2005
Wat
er ta
ble
dept
h (c
m b
elow
sur
face
)
125 166 175 179 187 196 203 210 217 224 232 238−4
−2
0
2WT 2006
Days
Fig. 5. Measured water table depth at Stordalen Mire for 2004–2006.
3221
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Fig. 6. Water table modelled with the MMWH Model for Stordalen Mire 2004–2006.
3222
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Simulated water table for Kytalyk
-7
-6
-5
-4
-3
-2
-1
0
1
2
2003 2004 2005 2006 2007
Measurement campains
Wate
r le
vel (c
m b
elo
w g
rou
nd
)
Measured WT
Simulated WT
Fig. 7. Water table modelled with the MMWH Model for Kytalyk site 2004–2006.
3223
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Feb 04 Sept 04 Mar 05 Oct 05 Apr 06 Oct 060
5
10
15
20
25
30Stordalen CH4 fluxes 2004−2006 with measured WT
CH
4 m
g m
−2
hr−
1
Measured CH4 fluxesSimulated CH4 fluxes
Fig. 8. Measured (red) and simulated (black) CH4 emissions for 2004–2006 at Stordalen mirewith measured water table (see Fig. 5).
3224
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Feb 04 Sept 04 Mar 05 Oct 05 Apr 06 Oct 060
2
4
6
8
10
12
14
16
18
20C
H4
mg
m−
2 hr
−1
Stordalen CH4 fluxes 2004−2006 with simulated WT
Measured CH4 fluxesSimulated CH4 fluxes
Fig. 9. Measured (red) and simulated (black) CH4 emissions for 2004–2006 at Stordalen mireusing the simulated water table from Fig. 7.
3225
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Kytalyk CH4 fluxes 2004-2006 with measured WT
0
5
10
15
20
25
30
35
2003 2004 2005 2006 2007
Measurement campains
CH
4 m
g m
-2 h
r-1
measured CH4
simulated CH4
Fig. 10. Average measured value (red) and simulated (black) CH4 emissions for 2004–2006 atKytalyk site using the measured water table.
3226
BGD
4, 3195–3227, 2007
Modelling CH4
emissions from arctic
wetlands
A. M. R. Petrescu et al.
Title Page
Abstract Introduction
Conclusions References
Tables Figures
◭ ◮
◭ ◮
Back Close
Full Screen / Esc
Printer-friendly Version
Interactive Discussion
EGU
Kytalyk CH4 fluxes 2004-2006 with simulated WT
0
5
10
15
20
25
30
35
2003 2004 2005 2006 2007
Measurement campains
CH
4 m
g m
-2 h
r-1
simulated CH4
measured CH4
Figure 11. Average measured value (red) and simulated (black) CH emissions for 2004-Fig. 11. Average measured value (red) and simulated (black) CH4 emissions for 2004–2006 atKytalyk site using the simulated water table.
3227